

import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, BatchEncoding, PLBartTokenizer, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
)

from ...test_tokenization_common import TokenizerTesterMixin


a_      =     get_tests_dir('fixtures/test_sentencepiece.model')


if is_torch_available():
			from transformers.models.plbart.modeling_plbart import shift_tokens_right

a_      =     5_0003
a_      =     5_0002






@require_sentencepiece
@require_tokenizers
class _UpperCamelCase				(				__A				,						unittest.TestCase ):
			'''simple docstring'''







			lowerCamelCase__							     =PLBartTokenizer
			lowerCamelCase__							     =None
			lowerCamelCase__							     =False
			def 				__UpperCamelCase			(      self				:			Optional[int]						)				->							Dict:

				"""simple docstring"""

				super().setUp()

				# We have a SentencePiece fixture for testing
				SCREAMING_SNAKE_CASE :   int					  =							PLBartTokenizer(a   ,   language_codes="base"   ,   keep_accents=a						)
				tokenizer.save_pretrained(self.tmpdirname						)
			def 				__UpperCamelCase			(      self				:			List[Any]						)				->							str:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE :   Dict					  =							PLBartTokenizer(a   ,   language_codes="base"   ,   keep_accents=a						)

				SCREAMING_SNAKE_CASE :   Union[str, Any]					  =							tokenizer.tokenize("This is a test"						)
				self.assertListEqual(a   ,   ["▁This", "▁is", "▁a", "▁t", "est"]						)

				self.assertListEqual(
				    tokenizer.convert_tokens_to_ids(a						)   ,   [value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]]   ,   )

				SCREAMING_SNAKE_CASE :   int					  =							tokenizer.tokenize("I was born in 92000, and this is falsé."						)
				self.assertListEqual(
				    a   ,   [
				        SPIECE_UNDERLINE + "I",
				        SPIECE_UNDERLINE + "was",
				        SPIECE_UNDERLINE + "b",
				        "or",
				        "n",
				        SPIECE_UNDERLINE + "in",
				        SPIECE_UNDERLINE + "",
				        "9",
				        "2",
				        "0",
				        "0",
				        "0",
				        ",",
				        SPIECE_UNDERLINE + "and",
				        SPIECE_UNDERLINE + "this",
				        SPIECE_UNDERLINE + "is",
				        SPIECE_UNDERLINE + "f",
				        "al",
				        "s",
				        "é",
				        ".",
				    ]   ,   )
				SCREAMING_SNAKE_CASE :   Optional[int]					  =							tokenizer.convert_tokens_to_ids(a						)
				self.assertListEqual(
				    a   ,   [
				        value + tokenizer.fairseq_offset
				        for value in [8, 21, 84, 55, 24, 19, 7, 2, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 2, 4]
				    ]   ,   )

				SCREAMING_SNAKE_CASE :   int					  =							tokenizer.convert_ids_to_tokens(a						)
				self.assertListEqual(
				    a   ,   [
				        SPIECE_UNDERLINE + "I",
				        SPIECE_UNDERLINE + "was",
				        SPIECE_UNDERLINE + "b",
				        "or",
				        "n",
				        SPIECE_UNDERLINE + "in",
				        SPIECE_UNDERLINE + "",
				        "<unk>",
				        "2",
				        "0",
				        "0",
				        "0",
				        ",",
				        SPIECE_UNDERLINE + "and",
				        SPIECE_UNDERLINE + "this",
				        SPIECE_UNDERLINE + "is",
				        SPIECE_UNDERLINE + "f",
				        "al",
				        "s",
				        "<unk>",
				        ".",
				    ]   ,   )

				SCREAMING_SNAKE_CASE :   List[str]					  =							tokenizer.vocab_size
				SCREAMING_SNAKE_CASE :   Optional[int]					  =							[tokenizer.convert_ids_to_tokens(a						) for x in range(end - 4   ,   a						)]

				self.assertListEqual(a   ,   ["__java__", "__python__", "__en_XX__", "<mask>"]						)

				SCREAMING_SNAKE_CASE :   Tuple					  =							"java.lang.Exception, python.lang.Exception, javascript, php, ruby, go"
				SCREAMING_SNAKE_CASE :   Any					  =							tokenizer(a						).input_ids
				self.assertEqual(
				    tokenizer.decode(a   ,   skip_special_tokens=a   ,   clean_up_tokenization_spaces=a						)   ,   a   ,   )






			def 				__UpperCamelCase			(      self				:			List[str]						)				->							int:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE :   Dict					  =							PLBartTokenizer(a   ,   language_codes="multi"   ,   keep_accents=a						)

				SCREAMING_SNAKE_CASE :   Tuple					  =							tokenizer.tokenize("This is a test"						)
				self.assertListEqual(a   ,   ["▁This", "▁is", "▁a", "▁t", "est"]						)

				self.assertListEqual(
				    tokenizer.convert_tokens_to_ids(a						)   ,   [value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]]   ,   )

				SCREAMING_SNAKE_CASE :   Tuple					  =							tokenizer.tokenize("I was born in 92000, and this is falsé."						)
				self.assertListEqual(
				    a   ,   [
				        SPIECE_UNDERLINE + "I",
				        SPIECE_UNDERLINE + "was",
				        SPIECE_UNDERLINE + "b",
				        "or",
				        "n",
				        SPIECE_UNDERLINE + "in",
				        SPIECE_UNDERLINE + "",
				        "9",
				        "2",
				        "0",
				        "0",
				        "0",
				        ",",
				        SPIECE_UNDERLINE + "and",
				        SPIECE_UNDERLINE + "this",
				        SPIECE_UNDERLINE + "is",
				        SPIECE_UNDERLINE + "f",
				        "al",
				        "s",
				        "é",
				        ".",
				    ]   ,   )
				SCREAMING_SNAKE_CASE :   int					  =							tokenizer.convert_tokens_to_ids(a						)
				self.assertListEqual(
				    a   ,   [
				        value + tokenizer.fairseq_offset
				        for value in [8, 21, 84, 55, 24, 19, 7, 2, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 2, 4]
				    ]   ,   )

				SCREAMING_SNAKE_CASE :   Optional[Any]					  =							tokenizer.convert_ids_to_tokens(a						)
				self.assertListEqual(
				    a   ,   [
				        SPIECE_UNDERLINE + "I",
				        SPIECE_UNDERLINE + "was",
				        SPIECE_UNDERLINE + "b",
				        "or",
				        "n",
				        SPIECE_UNDERLINE + "in",
				        SPIECE_UNDERLINE + "",
				        "<unk>",
				        "2",
				        "0",
				        "0",
				        "0",
				        ",",
				        SPIECE_UNDERLINE + "and",
				        SPIECE_UNDERLINE + "this",
				        SPIECE_UNDERLINE + "is",
				        SPIECE_UNDERLINE + "f",
				        "al",
				        "s",
				        "<unk>",
				        ".",
				    ]   ,   )
				SCREAMING_SNAKE_CASE :   List[Any]					  =							tokenizer.vocab_size
				SCREAMING_SNAKE_CASE :   Dict					  =							[tokenizer.convert_ids_to_tokens(a						) for x in range(end - 7   ,   a						)]

				self.assertListEqual(
				    a   ,   ["__java__", "__python__", "__en_XX__", "__javascript__", "__php__", "__ruby__", "__go__"]						)
				SCREAMING_SNAKE_CASE :   List[Any]					  =							"java.lang.Exception, python.lang.Exception, javascript, php, ruby, go"
				SCREAMING_SNAKE_CASE :   Union[str, Any]					  =							tokenizer(a						).input_ids
				self.assertEqual(
				    tokenizer.decode(a   ,   skip_special_tokens=a   ,   clean_up_tokenization_spaces=a						)   ,   a   ,   )






@require_torch
@require_sentencepiece
@require_tokenizers
class _UpperCamelCase				(				unittest.TestCase ):
			'''simple docstring'''







			lowerCamelCase__							     ='uclanlp/plbart-python-en_XX'
			lowerCamelCase__							     =[
			    'def maximum(a,b,c):NEW_LINE_INDENTreturn max([a,b,c])',
			    'def sum(a,b,c):NEW_LINE_INDENTreturn sum([a,b,c])',
			]
			lowerCamelCase__							     =[
			    'Returns the maximum value of a b c.',
			    'Sums the values of a b c.',
			]
			lowerCamelCase__							     =[
			    134,
			    5452,
			    33460,
			    33441,
			    33463,
			    33465,
			    33463,
			    33449,
			    988,
			    20,
			    33456,
			    19,
			    33456,
			    771,
			    39,
			    4258,
			    889,
			    3318,
			    33441,
			    33463,
			    33465,
			    33463,
			    33449,
			    2471,
			    2,
			    PYTHON_CODE,
			]
			@classmethod
			def 				__UpperCamelCase			(      cls				:			int						)				->							Tuple:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE :   PLBartTokenizer					  =							PLBartTokenizer.from_pretrained(
				    cls.checkpoint_name   ,   language_codes="base"   ,   src_lang="python"   ,   tgt_lang="en_XX"						)
				SCREAMING_SNAKE_CASE :   Optional[int]					  =							1
				return cls
			def 				__UpperCamelCase			(      self				:			Any						)				->							Optional[int]:

				"""simple docstring"""

				self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["__java__"]   ,   5_0001						)
				self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["__python__"]   ,   5_0002						)
				self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["__en_XX__"]   ,   5_0003						)
			def 				__UpperCamelCase			(      self				:			int						)				->							Optional[int]:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE :   str					  =							self.tokenizer.batch_encode_plus(self.src_text						).input_ids[0]
				self.assertListEqual(self.expected_src_tokens   ,   a						)
			def 				__UpperCamelCase			(      self				:			Optional[Any]						)				->							Optional[Any]:

				"""simple docstring"""

				self.assertIn(a   ,   self.tokenizer.all_special_ids						)
				SCREAMING_SNAKE_CASE :   Dict					  =							[EN_CODE, 9037, 3_3442, 57, 752, 153, 14, 56, 18, 9, 2]
				SCREAMING_SNAKE_CASE :   str					  =							self.tokenizer.decode(a   ,   skip_special_tokens=a						)
				SCREAMING_SNAKE_CASE :   List[str]					  =							self.tokenizer.decode(generated_ids[1:]   ,   skip_special_tokens=a						)
				self.assertEqual(a   ,   a						)
				self.assertNotIn(self.tokenizer.eos_token   ,   a						)
			def 				__UpperCamelCase			(      self				:			Optional[Any]						)				->							Union[str, Any]:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE :   Dict					  =							["def sum(a,b,c):NEW_LINE_INDENTreturn sum([a,b,c])" * 20]
				self.assertIsInstance(src_text[0]   ,   a						)
				SCREAMING_SNAKE_CASE :   Optional[int]					  =							10
				SCREAMING_SNAKE_CASE :   Dict					  =							self.tokenizer(a   ,   max_length=a   ,   truncation=a						).input_ids[0]
				self.assertEqual(ids[-2]   ,   2						)
				self.assertEqual(ids[-1]   ,   a						)
				self.assertEqual(len(a						)   ,   a						)
			def 				__UpperCamelCase			(      self				:			str						)				->							str:

				"""simple docstring"""

				self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["<mask>", "__java__"]						)   ,   [5_0004, 5_0001]						)
			def 				__UpperCamelCase			(      self				:			List[str]						)				->							int:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE :   List[Any]					  =							tempfile.mkdtemp()
				SCREAMING_SNAKE_CASE :   Any					  =							self.tokenizer.fairseq_tokens_to_ids
				self.tokenizer.save_pretrained(a						)
				SCREAMING_SNAKE_CASE :   Dict					  =							PLBartTokenizer.from_pretrained(a						)
				self.assertDictEqual(new_tok.fairseq_tokens_to_ids   ,   a						)
			@require_torch
			def 				__UpperCamelCase			(      self				:			Tuple						)				->							List[Any]:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE :   List[str]					  =							self.tokenizer(self.src_text   ,   text_target=self.tgt_text   ,   padding=a   ,   return_tensors="pt"						)
				SCREAMING_SNAKE_CASE :   Optional[Any]					  =							shift_tokens_right(batch["labels"]   ,   self.tokenizer.pad_token_id						)

				# fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
				self.assertEqual(batch.input_ids[1][-2:].tolist()   ,   [2, PYTHON_CODE]						)
				self.assertEqual(batch.decoder_input_ids[1][0]   ,   a						)
				self.assertEqual(batch.decoder_input_ids[1][-1]   ,   2						)
				self.assertEqual(batch.labels[1][-2:].tolist()   ,   [2, EN_CODE]						)
			@require_torch
			def 				__UpperCamelCase			(      self				:			Union[str, Any]						)				->							Any:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE :   Any					  =							self.tokenizer(
				    self.src_text   ,   text_target=self.tgt_text   ,   padding=a   ,   truncation=a   ,   max_length=len(self.expected_src_tokens						)   ,   return_tensors="pt"   ,   )
				SCREAMING_SNAKE_CASE :   Tuple					  =							shift_tokens_right(batch["labels"]   ,   self.tokenizer.pad_token_id						)

				self.assertIsInstance(a   ,   a						)

				self.assertEqual((2, 26)   ,   batch.input_ids.shape						)
				self.assertEqual((2, 26)   ,   batch.attention_mask.shape						)
				SCREAMING_SNAKE_CASE :   Union[str, Any]					  =							batch.input_ids.tolist()[0]
				self.assertListEqual(self.expected_src_tokens   ,   a						)
				self.assertEqual(2   ,   batch.decoder_input_ids[0, -1]						)  # EOS
				# Test that special tokens are reset
				self.assertEqual(self.tokenizer.prefix_tokens   ,   []						)
				self.assertEqual(self.tokenizer.suffix_tokens   ,   [self.tokenizer.eos_token_id, PYTHON_CODE]						)
			def 				__UpperCamelCase			(      self				:			Dict						)				->							str:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE :   Optional[int]					  =							self.tokenizer(self.src_text   ,   padding=a   ,   truncation=a   ,   max_length=3   ,   return_tensors="pt"						)
				SCREAMING_SNAKE_CASE :   List[str]					  =							self.tokenizer(
				    text_target=self.tgt_text   ,   padding=a   ,   truncation=a   ,   max_length=10   ,   return_tensors="pt"						)
				SCREAMING_SNAKE_CASE :   Union[str, Any]					  =							targets["input_ids"]
				SCREAMING_SNAKE_CASE :   Dict					  =							shift_tokens_right(a   ,   self.tokenizer.pad_token_id						)

				self.assertEqual(batch.input_ids.shape[1]   ,   3						)
				self.assertEqual(batch.decoder_input_ids.shape[1]   ,   10						)






			@require_torch
			def 				__UpperCamelCase			(      self				:			Optional[int]						)				->							Any:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE :   Dict					  =							self.tokenizer._build_translation_inputs(
				    "A test"   ,   return_tensors="pt"   ,   src_lang="en_XX"   ,   tgt_lang="java"						)

				self.assertEqual(
				    nested_simplify(a						)   ,   {
				        # A, test, EOS, en_XX
				        "input_ids": [[150, 242, 2, 5_0003]],
				        "attention_mask": [[1, 1, 1, 1]],
				        # java
				        "forced_bos_token_id": 5_0001,
				    }   ,   )
from __future__ import annotations
class SCREAMING_SNAKE_CASE_		:







   def __init__(     self						:						Dict   ,   lowerCamelCase_						:						str   ,   lowerCamelCase_						:						str				):





    """simple docstring"""


    UpperCamelCase  ,     UpperCamelCase			  =      text, pattern
    UpperCamelCase  ,     UpperCamelCase			  =      len(lowerCamelCase_				), len(lowerCamelCase_				)







   def 						lowerCamelCase_	(     self						:						List[Any]   ,   lowerCamelCase_						:						str				):





    """simple docstring"""


    for i in range(self.patLen - 1   ,   -1   ,   -1				):
     if char == self.pattern[i]:
      return i
    return -1







   def 						lowerCamelCase_	(     self						:						Union[str, Any]   ,   lowerCamelCase_						:						int				):





    """simple docstring"""


    for i in range(self.patLen - 1   ,   -1   ,   -1				):
     if self.pattern[i] != self.text[current_pos + i]:
      return current_pos + i
    return -1







   def 						lowerCamelCase_	(     self						:						Union[str, Any]				):





    """simple docstring"""


    UpperCamelCase			  =      []
    for i in range(self.textLen - self.patLen + 1				):
     UpperCamelCase			  =      self.mismatch_in_text(lowerCamelCase_				)
     if mismatch_index == -1:
      positions.append(lowerCamelCase_				)
     else:
      UpperCamelCase			  =      self.match_in_pattern(self.text[mismatch_index]				)
      UpperCamelCase			  =      (
          mismatch_index - match_index
      )  # shifting index lgtm [py/multiple-definition]
    return positions





_SCREAMING_SNAKE_CASE 		=      """ABAABA"""
_SCREAMING_SNAKE_CASE 		=      """AB"""
_SCREAMING_SNAKE_CASE 		=      BoyerMooreSearch(text, pattern)
_SCREAMING_SNAKE_CASE 		=      bms.bad_character_heuristic()

if len(positions) == 0:
     print("""No match found""")
else:
     print("""Pattern found in following positions: """)
     print(positions)
